You're viewing version 2.14 of the OpenSearch documentation. This version is no longer maintained. For the latest version, see the current documentation. For information about OpenSearch version maintenance, see Release Schedule and Maintenance Policy.

Text field type

A text field type contains a string that is analyzed. It is used for full-text search because it allows partial matches. Searches for multiple terms can match some but not all of them. Depending on the analyzer, results can be case insensitive, stemmed, have stopwords removed, have synonyms applied, and so on.

If you need to use a field for exact-value search, map it as a keyword instead.

The match_only_text field is a space-optimized version of the text field. If you don’t need to query phrases or use positional queries, map the field as match_only_text instead of text. Positional queries are queries in which the position of the term in the phrase is important, such as interval or span queries.

Example

Create a mapping with a text field:

PUT movies
{
  "mappings" : {
    "properties" : {
      "title" : {
        "type" :  "text"
      }
    }
  }
}

Parameters

The following table lists the parameters accepted by text field types. All parameters are optional.

Term vector parameter

A term vector is produced during analysis. It contains:

• A list of terms.
• The ordinal position of each term.
• The start and end character offsets of the search string within the field.
• Payloads (if available). Each term can have custom binary data associated with the term’s position.

The term_vector field contains a JSON object that accepts the following parameters:

Storing positions is useful for proximity queries. Storing character offsets is useful for highlighting.

Term vector parameter example

Create a mapping with a text field that stores character offsets in a term vector:

PUT testindex
{
  "mappings" : {
    "properties" : {
      "dob" : {
        "type" :  "text",
        "term_vector": "with_positions_offsets"
      }
    }
  }
}

Index a document with a text field:

PUT testindex/_doc/1
{
    "dob" : "The patient's date of birth."
}

Query for “date of birth” and highlight it in the original field:

GET testindex/_search
{
  "query": {
    "match": {
      "text": "date of birth"
    }
  },
  "highlight": {
    "fields": {
      "text": {} 
    }
  }
}

The words “date of birth” are highlighted in the response:

{
  "took" : 854,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.8630463,
    "hits" : [
      {
        "_index" : "testindex",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 0.8630463,
        "_source" : {
          "text" : "The patient's date of birth."
        },
        "highlight" : {
          "text" : [
            "The patient's <em>date</em> <em>of</em> <em>birth</em>."
          ]
        }
      }
    ]
  }
}